Explore 15 essential MCP servers for web developers to enhance AI workflows with tools, data, and automation.
Learn when streaks improve retention, when they create fragile engagement, and how PMs can design healthier systems around user progress.
Learn how to build a harness-style AI workflow using Claude Code with specialized Dev, QE, and Ops subagents, gated handoffs, MCP telemetry, and LEARNING.md.
Compare the top AI development tools and models of July 2026. View updated rankings, feature breakdowns, and find the best fit for you.
Learn how to detect unused and ghost dependencies in JavaScript projects using Knip, a project-level linter that keeps your dependency graph accurate.
Learn how Storybook MCP enables AI agents to understand your component library, generate accurate UI, and validate code using documentation, stories, and automated tests.
Debug RSC hydration mismatches in production with Next.js instrumentation, Suspense isolation, HTML diffing, and CI smoke tests.
Learn how PMs can use AI evals to diagnose output quality issues, set pass criteria, and improve AI features with less guesswork.
Explore why npm dependencies are a major supply chain security risk and how to protect JavaScript apps from compromised packages and transitive threats.
Enabled React Compiler v1.0 on a production Next.js app. Here’s every warning, breakage, and silent opt-out I documented — and what actually worked.
I was working with an intern on a UX research project, and before we even started, we both had private […]
We built the same app in TanStack Start RSC and Next.js RSC. TanStack shipped 40% less JS and built 4x faster — but Next.js is still the safer production bet.
